Evidence map›Paper›PMID 41963482›Full record

ArticleScientific reports2026

Factors influencing user adoption of AI painting tools based on the AIDUA model.

Yang Li, Hwee Ling Siek, JinLing Guo

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yang LiSchool of Fashion Media, Jiangxi Institute of Fashion Technology, Nanchang City, Jiangxi Province, China.
Hwee Ling SiekDe Institute of Creative Arts and Design, UCSI University, Kuala Lumpur, Malaysia. siekhl@ucsiuniversity.edu.my.
JinLing GuoBusiness School, Jiangxi Institute of Fashion Technology, Nanchang City, Jiangxi Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence painting tools (AIPT) are increasingly integrated into creative practices, yet designers' willingness to adopt them remains underexplored. This study applies the artificial intelligence device use acceptance (AIDUA) model, grounded in cognitive appraisal theory, to investigate factors influencing designers' acceptance of AIPT. Using survey data from 480 respondents and structural equation modeling (SEM), we examined the interplay of supportive factors (perceived usefulness (PU), hedonic motivation (HM), social influence (SI), trust (TRU)) and opposing factors (perceived risk (PR)). Results indicate that hedonic motivation significantly reduces PR, while social consensus enhances trust, both of which shape attitude (ATT) and intentions toward AIPT. Theoretically, this study extends AIDUA to the creative domain, highlighting its value for explaining ambivalent adoption behavior. Practically, the findings provide actionable insights for developers and educators to enhance AIPT acceptance by addressing risk perceptions, improving transparency, and fostering supportive user communities.

Identifiers

PMID41963482
PMCPMC13230577

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.